US20060203964A1  Method and device for calculating the radiation dose distribution for a radiation treatment system for the purpose of radiation therapy of an animal body  Google Patents
Method and device for calculating the radiation dose distribution for a radiation treatment system for the purpose of radiation therapy of an animal body Download PDFInfo
 Publication number
 US20060203964A1 US20060203964A1 US11/299,891 US29989105A US2006203964A1 US 20060203964 A1 US20060203964 A1 US 20060203964A1 US 29989105 A US29989105 A US 29989105A US 2006203964 A1 US2006203964 A1 US 2006203964A1
 Authority
 US
 United States
 Prior art keywords
 μ
 radiation
 beam
 dose
 calculating
 Prior art date
 Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
 Granted
Links
Images
Classifications

 A—HUMAN NECESSITIES
 A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
 A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
 A61N5/00—Radiation therapy
 A61N5/10—Xray therapy; Gammaray therapy; Particleirradiation therapy
 A61N5/103—Treatment planning systems
 A61N5/1031—Treatment planning systems using a specific method of dose optimization

 G—PHYSICS
 G01—MEASURING; TESTING
 G01T—MEASUREMENT OF NUCLEAR OR XRADIATION
 G01T1/00—Measuring Xradiation, gamma radiation, corpuscular radiation, or cosmic radiation
 G01T1/29—Measurement performed on radiation beams, e.g. position or section of the beam; Measurement of spatial distribution of radiation

 A—HUMAN NECESSITIES
 A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
 A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
 A61N5/00—Radiation therapy
 A61N5/10—Xray therapy; Gammaray therapy; Particleirradiation therapy
 A61N5/103—Treatment planning systems
 A61N5/1031—Treatment planning systems using a specific method of dose optimization
 A61N2005/1034—Monte Carlo type methods; particle tracking
Abstract
Description
 The invention relates to a method for calculating the radiation dose distribution for a radiation treatment system for the purpose of radiation therapy of an animal body, wherein said radiation beam of the radiation treatment system exhibits a specific beam field size and shape at different depths.
 The invention also relates to a device for calculating the radiation dose distribution for a radiation treatment system for the purpose of radiation therapy of an animal body, wherein said radiation beam of the radiation treatment system exhibits a specific beam field size and shape at different depths.
 Calculation accuracy of the radiation dose distribution for the purpose of radiation therapy has been significantly improved during the last decades. The development has gone from simple factor based calculations done manually by clinical physicists to calculations with sophisticated algorithms embedded in commercial treatment planning systems. The present clinical problem is not as much the calculation of the dose distribution, as how to verify the results of the treatment planning system.
 The risk for errors in the software used in treatment planning systems increases with the complexity of the algorithms and its applications. There can be bugs in the programming code or errors made by the users. An independent check of the results is desirable/required. In addition, as the accuracy of the treatment planning system improves, the verification mechanism should be able to catch smaller and smaller errors.
 The most critical treatment parameter to be checked is the number of monitor units (M) assigned per field (segment) to yield the desired dose. The verification of the number of M for a specific dose can be done using a water phantom geometry, and can be based on tables of measurements, a model, or a combination. The fundamental parameter in the M calculation procedure is the relation between the dose per M to the target and the dose per M to a reference geometry. This relation can include a transition in depth, a change in field size and shape, a wedge, and objects in the field such as blocks and the block holder.
 In principle the number of M can be calculated using a factor based model where the number of transitions is e.g. mapped to factors, e.g. tissue phantom ratio (T), a head scatter factor (S_{c}) and a phantom scatter factor (S_{p}). The factors can be tabulated as functions of the field settings, but the irregular shaped fields commonly used impose to large variability to be practically to manage. To make the check applicable for general field shapes some sort of scatter integration must be used.
 It is an object of the invention to provide a method and device according to the above allowing the calculation of a radiation dose distribution for a radiation treatment system using a limited amount of data whilst preserving the required accuracy.
 According to the invention the method is characterized by the steps of
 i) determining at least one beam quality index being representative for said radiation beam being used, and
 ii) calculating said radiation dose distribution in said specific beam field using parameterized dose deposition kernels based on said at least one beam quality index.
 According to an aspect of the invention the method is further characterized by the steps of
 iii) using for different devices precollected measured radiation beam data, said measured radiation beam data comprising:
 a) measured phantom dose data at different depths, for different field shapes and sizes and at different energies;
 b) calculated dose deposition kernel parameters;
 c) measured head scatter factors and output factors that can be transformed into phantom scatter factors for the corresponding field sizes,
 iv) determining said at least one beam quality index according to step
 i) using the precollected measured radiation beam data according to step iii);
 v) associating the dose deposition kernel parameters to said one or a few beam quality index being determined.
 According to a furhter embodiment the method according to the invention is further characterized by the step of vi) using Monte Carlo simulations to simulate said measured data according to step iii).
 In a further embodiment the at least one quality index is determined by the ratio between the tissue phantom ratio (TPR) measured at d_{1}=20 cm and d_{2}=10 cm depth (TPR_{20,10}).
 In another embodiment the at least one beam quality index is determined by the percentage depth dose (PDD) at d_{3}=10 cm (PDD_{10}).
 In another advantageous embodiment the method according to the invention is characterized in that the dose deposition kernels are pencil dose deposition kernels.
 In yet another advantageous embodiment the method according to the invention is characterized in that the dose deposition kernels are point dose deposition kernels.
 The device according to the invention further comprising inputting means arranged for inputting at least one beam quality index being representative for said radiation beam being used to calculating means, said calculating means being arranged for calculating said radiation dose distribution using parameterized dose deposition kernels being based on said at least one beam quality index.
 In one preferred embodiment the device is a monitor unit (MU) checking device, whereas in another embodiment the device is a IMRT treatment MU checking device.
 The invention will now be described by means of some examples shown in the accompanying Figures, which show in:

FIG. 1 a comparison between the original tabulated pencil beam parameters and the ones calculated out of equation nos. 3, 4, 5 and 6 for an arbitrary chosen 10 MV accelerator; 
FIG. 2 error plots for low energies (210 accelerators), mostly 5 and 6 MV beams, wherein the errors are normalized in a small interval around 10 cm in the 10×10 cm^{2 }field; 
FIG. 3 error plots for high energies (138 accelerators), mostly 1518 MV beams, wherein the errors are normalized in a small interval around 10 cm in the 10×10 cm^{2 }field; and 
FIG. 4 error plots for 10×10 cm^{2 }fields for very low energy (35 MV, 25 accelerators), medium energy (810 MV, 173 accelerators) and very high energy (1825 MV, 88 accelerators), wherein the plots are normalized in a small interval around 10 cm depth.  For implementing the method according to the invention data from different radiation treatment units have been used to determine the calculation model. Each data set for a treatment unit includes depth dose measurements from surface down to 35 cm depth in four field sizes (5×5 cm^{2}, 10×10 cm^{2}, 15×15 cm^{2 }and 20×20 cm^{2}), all with a Source Surface Distance (SSD) equal to 90 cm. Furthermore, measured head scatter factors and output factors are included, which can be transformed into phantom scatter factors for the three field sizes (5×5 cm^{2}, 15×15 cm^{2 }and 20×20 cm^{2}) at 10 cm depth with a SSD=90 cm. The data collection also includes calculated pencil beam parameters.
 For the purpose of deriving the data parameterization according to the invention more than 1000 data sets from around 800 radiation treatment devices were included.
 The calculation of TPR_{20,10 }is based on the depth dose value at 10 and 20 cm depth. An inverse square correction was done, with the assumption that all the radiation is emitted from the same point (the target). The correction for the changed field size at 20 cm depth was done using the phantom scatter factor for an 11×11 cm field. This value was calculated using a second degree fitting to the phantom scatter factors for 5×5 cm^{2}, 10×10 cm^{2}, and 15×15 cm^{2 }field sizes.
 The pencil beam model used from a known commercial treatment planning system is based on a four parameter kernel to describe the primary and scatter part of the dose as a function of the distance to the kernel central axis. Actually three more parameters are used in that treatment planning system to fine tune the fitted results to better conserve the primary/scatter ratio given by the Monte Carlo data and to adjust for small machine individual variations.
 In order to construct a simple model, those type of corrections are omitted when implementing the method according to the present invention in a device according to the invention. The kernel value as a function of the distance to the kernel central axis r is expressed as:
$\begin{array}{cc}k\left(r,z\right)=\frac{A\left(z\right)\mathrm{exp}\text{\hspace{1em}}\left[a\left(z\right)r\right]+B\left(z\right)\mathrm{exp}\text{\hspace{1em}}\left[b\left(z\right)r\right]}{r}& \left(1\right)\end{array}$  where z is the calculation depth and A, B, a, and b are depth dependent parameters. The four parameters are calculated from Monte Carlo simulations with an energy spectra derived from depth dose measurements and measured phantom scatter values. The primary part and the scatter part are separated, such that the first exponential takes care of the primary part and the second takes care of the scatter part.
 When the treatment planning system uses the model, the four parameters are tabulated as a function of the depth from 0.075 cm below the surface to below 40 cm, in steps of 0.075 cm.
 The kernel as formulated in equation (1) can be integrated over a circular field with radius R to get the dose per energy fluence at the central axis:
$\begin{array}{cc}\begin{array}{c}D\left(R,z\right)=2\text{\hspace{1em}}\pi {\int}_{0}^{R}\Psi \left(r\right)k\left(r,z\right)r\text{\hspace{1em}}dr\\ =2\text{\hspace{1em}}\pi \text{\hspace{1em}}\Psi [\frac{A}{a}\left(z\right)\left[1\mathrm{exp}\text{\hspace{1em}}\left[a\left(z\right)R\right]\right]+\\ \frac{B}{b}\left(z\right)\left[1\mathrm{exp}\text{\hspace{1em}}\left[b\left(z\right)R\right]\right]]\end{array}& \left(2\right)\end{array}$  where the energy fluence is assumed to be constant.
 The ratio 2ΠA/a has a clear physical meaning, it describes the primary part of the dose per energy fluence for an infinite field radius. The ratio 2ΠB/b analogously describes the scatter part for an infinite field. Hence, it is more convenient to work with the parameters A/a, B/b, a and b in an attempt to make a depth parameterization, rather then with A, B, a and b directly.
 The depth parameterization functions for the primary and scatter part for infinite fields are:
$\begin{array}{cc}\frac{A}{a}={A}_{1}\left[1\mathrm{exp}\text{\hspace{1em}}\left[{A}_{2}\sqrt{{z}^{2}+{A}_{5}^{2}}\right]\right]\mathrm{exp}\text{\hspace{1em}}\left[{A}_{3}z+{A}_{4}{z}^{2}\right]\text{}\mathrm{and}& \left(3\right)\\ \frac{B}{b}={B}_{1}\left[1\mathrm{exp}\text{\hspace{1em}}\left[{B}_{2}\sqrt{{z}^{2}+{B}_{5}^{2}}\right]\right]\mathrm{exp}\text{\hspace{1em}}\left[{B}_{3}z+{B}_{4}{z}^{2}\right]& \left(4\right)\end{array}$  where A_{1}, A_{2}, A_{3}, A_{4}, A_{5}, B1, B_{2}, B_{3}, B_{4 }and B_{5 }are fitting parameters. The parameters A_{1}, and B_{1 }are for normalization, and are used to get a correct relation between the primary and scatter part of the dose. The parameter −A_{2 }resembles a linear attenuation coefficient for the primary electrons and −B_{2 }one for the scattered photons. The parameters −A_{3 }and −B_{3 }can be seen as the linear attenuation coefficient for the primary photons.
 The parameters A_{4 }and B_{4 }introduce a beam hardening correction. Due to mismatching between the original and the fitted data at shallow depths, we introduced the correction parameters A_{5 }and B_{5 }which have two purposes, they introduce back scattering and slightly extend the build up region. The physical factor that this extension corrects for is the change in mean direction of the secondary particles with depth. At shallow depths the electrons and the scattered photons are more forwardly directed then at deep depths.
 The effect on the shape of depth parameterization function for the primary part is limited when A_{5 }is introduced, but for the scatter part the change with B_{5 }is significant. The calculations of the parameters were not done to get the right values according to the interpretations of the parameters. In other words, no effort were made to get, for example, A_{3 }close to the “real” linear attenuation coefficient, the goal was to find the best values of the parameters to fit the functions to the tabled values.
 The expression 1exp[a(z)R] in equation (2) is the ratio between the primary dose to the central axis with a circular field of radius R and that of an infinite field. This ratio is only weakly depth dependent except in the buildup region, which means that a(z) is only weakly depth dependent. Hence, a is parameterized as a linear function of the depth.
a=a _{1} +a _{2} z (5)  where a_{1 }and a_{2 }are fitting parameters.
 The expression 1exp[−b(z)R] in equation (2) can analogously be interpreted as the ratio between the scatter dose to the central axis with a circular field of radius R and an infinite field. It turned out that it was possible to use the same fitting function for b as for A/a and B/b.
$\begin{array}{cc}b={b}_{1}\left[1\mathrm{exp}\text{\hspace{1em}}\left[{b}_{2}\sqrt{{z}^{2}+{b}_{5}^{2}}\right]\right]\mathrm{exp}\text{\hspace{1em}}\left[{b}_{3}z+{b}_{4}{z}^{2}\right]& \left(6\right)\end{array}$  where b_{1}, b_{2}, b_{3}, b_{4 }and b_{5 }are fitting parameters.
 The parameters of the chosen functions were fitted to the tabulated data extracted from the database containing said premeasured radiation beam data for all the radiation treatment systems and energies. The fitting step was performed in a stepwise procedure using a script written specially for this purpose. The parameters A_{3 }and A_{4 }were determined from the slope at great depths, A_{2 }was set to get the maximum point at the right position, A_{1}, was set to yield a correct value at 10 cm depth, and A_{5 }to minimize the error just below the surface.
 The same method was used for B/b and b, except that B_{3 }was set equal to A_{3 }and B_{4 }equal to A_{4}. The parameters a_{1 }and a_{2 }was found using least square fitting below the build up region for the primary part.
 The disagreement between the fitted curve and the a data (
FIG. 1 ) at shallow depths are not very critical since the model is not intended to be used at shallow depth due to the electron contamination problem. The parameterization of b starts to disagree at depths somewhere between 30 cm and 40 cm, which are deeper than for normal treatments.  The seventeen accelerator and energy specific parameters are not explicitly measurable, which means they have to be related to some measurable quantity or calculated through fitting of the entire model against measurements. The first way is preferable, if the precision allows it, as it does not demand a large quantity of measured data for each accelerator and energy. It turned out that the parameters could be calculated with good precision as polynomial functions of the beam quality index TPR_{20,10 }as described in claim 9.
 The parameters in the polynomial functions were adjusted to minimize the deviation between the model and depth doses calculated with the original pencil beam parameters.
 The model was tested as a predictor of the ratio between the dose at the central axis for different depths and field sizes and the dose to a reference point (a 10×10 cm^{2 }field at 10 cm depth with SSD=90 cm):
$\begin{array}{cc}\begin{array}{c}{D}_{\text{\hspace{1em}}\mathrm{ratio}}\left(z,s\right)=\frac{D\left(z,s\right)}{D\left({z}_{\mathrm{ref}},{s}_{\mathrm{ref}}\right)}\\ ={\left[\frac{\mathrm{SSD}+{z}_{\mathrm{ref}}}{\mathrm{SSD}+z}\right]}^{2}\frac{2\text{\hspace{1em}}\pi \text{\hspace{1em}}{\int}_{0}^{R\left(z,s\right)}k\left(r,z,{\mathrm{TPR}}_{20.10}\right)r\text{\hspace{1em}}dr}{2\text{\hspace{1em}}\pi \text{\hspace{1em}}{\int}_{0}^{R\left({z}_{\mathrm{ref}},{s}_{\mathrm{ref}}\right)}k\left(r,z,{\mathrm{TPR}}_{20.10}\right)r\text{\hspace{1em}}dr}\end{array}& \left(7\right)\end{array}$  where k (r,z,TPR_{20,10}) is the pencil beam kernel according to equation (1) with a TPR_{20,10 }dependence. The integration limit R(z,s) is calculated as a function of the side length s of the square fields and of the depth
$\begin{array}{cc}R\left(z,s\right)=0.561\left[\frac{\mathrm{SSD}+z}{\mathrm{SSD}+{z}_{\mathrm{ref}}}\right]s& \left(8\right)\end{array}$  where the constant factor is from the relation between square fields and their equivalent circular fields.
 The great number of measurements within the data set has made it possible to make reliable estimations of the expected deviations between clinical measurements and the model.
FIGS. 2, 3 , 4 give the median deviation, surrounded by indicators that delimit 50% and 90% of the accelerators. The accelerators are divided in 5 groups depending on their TPR_{20,10 }ratio:  I Very low energy−TPR_{20,10}=[0.61, 0.645]
 II Low energy−TPR_{20,10}=[0.645, 0.682]
 III Medium energy−TPR_{20,10}=[0.682, 0.744]
 IV High energy−TPR_{20,10}=[0.744, 0.772]
 V Very high energy−TPR_{20,10}=[0.772, 0.81]
 Systematic deviation between model and data can be visualized by the median error in
FIGS. 2, 3 and 4, while the random error can be visualized by the width of the 50% and 90% confidence intervals in the same plots. Both types of errors can originate from both the measurements and the model itself. Systematic errors in measured data will not be considered further in this discussion as the data were acquired by different researchers independently and with varying equipment.  Lack of modelling for electron contamination is the reason for the underestimation of the dose for shallow depths at high energies while shape limitations is likely the reason for the slight overestimation of the phantom scatter factors by up to 1% for practically all field sizes that differ from 10×10 cm^{2}. This effect is present for all energies but is most significant for the lowest energies.
 The device is based on the assumption that the difference in dose distribution between two beams with the same TPR_{20,10 }is small. Analysis of the error plots indicates that this assumption is true. The width of the confidence intervals originates from both individuality between accelerators with the same TPR_{20,10}, and from random errors in measurements. The dose data stems from three different measurements, i.e. depth dose, output factors in water, and output factors in air, all contributing to the random error of measured data.
 The magnitude of the depth dose error can be estimated from the error plots for 10×10 cm^{2 }fields (
FIGS. 2 b, 3 b, 4ac). The plots are normalized in a small interval around 10 cm depth and the width of the confidence intervals just around this interval is mainly due to random errors. With this width subtracted it is possible to conclude that the individuality of the accelerators with respect to depth doses has the magnitude of tenth of a percent (except for shallow depths, and very low energies). It is more difficult to draw any conclusions of the degree of individuality in the field size dependence, as no measurements just around the 10×10 cm field were available.  But the fact that the width of the confidence intervals for 5×5 cm^{2}, 15×15 cm^{2 }and 20×20 cm^{2 }fields do not differ more than they do, indicates that the random errors in the measurements are the main contributor to the spread in the plots. One can also draw a conclusion about the poor quality of TPR_{20,10 }as a predictor of dose calculation parameters for shallow depths and very low energies. In these cases a distinct depth dependence of the random deviations between the calculated and measured dose can be seen, but the effect of electron contamination and increasing random error in the depth dose measurements at shallow depths should also be taken into account. TPR_{20,10 }as beam quality parameter with shallow depth aspects have been previously discussed, but in another context.
 From
FIG. 4 a it seems that the model is less accurate at very low energies showing both systematic and random deviations from the measurements. It should be noticed that the number of accelerators in the group with very low energy is much smaller than in the other groups and at least the 90% confidence interval is based on too few accelerators to be reliable.  The design of the model does also allow varying beam quality specifications as all parameters are expressed through μ (see claim 8), which absolute value is close to the linear attenuation coefficient. By adjusting μ and make it a function of the position in the field, it would be possible to make a first order correction for off axis softening, or beam hardening due to a metal wedge.
 It surprisingly appeared that when using the method according to the invention TPR_{20,10 }is useful as a predictor of dose calculation parameters at depths deeper than the range of contaminating electrons.
 The pencil beam model with parameterized depth dependence according to the method and device of the present invention fulfills the requirements for a monitor unit verification tool for modern radiotherapy. With a calculation software using an integration algorithm, the central axis doses can be calculated with an accuracy of 2% (disregarding head scatter) for arbitrary field shapes and depths within certain limits.
 The method according to the invention is tested for field sizes between 5×5 cm^{2 }and 20×20 cm^{2}. The depth should be deeper than the range of contaminating electrons. In most cases, the error will be smaller. The reliability of the given number of monitor units or of the dose can be presented together with the result. This quality can be useful in the clinical work, even at other occasions than verification.
Claims (12)
Priority Applications (2)
Application Number  Priority Date  Filing Date  Title 

EP04078493.6  20041223  
EP04078493A EP1674129B1 (en)  20041223  20041223  Method and device for calculating the radiation dose distribution for a radiation treatment system for the purpose of radiation therapy of an animal body 
Publications (2)
Publication Number  Publication Date 

US20060203964A1 true US20060203964A1 (en)  20060914 
US7542545B2 US7542545B2 (en)  20090602 
Family
ID=34928770
Family Applications (1)
Application Number  Title  Priority Date  Filing Date 

US11/299,891 Expired  Fee Related US7542545B2 (en)  20041223  20051213  Method and device for calculating the radiation dose distribution for a radiation treatment system for the purpose of radiation therapy of an animal body 
Country Status (10)
Country  Link 

US (1)  US7542545B2 (en) 
EP (1)  EP1674129B1 (en) 
JP (1)  JP4936723B2 (en) 
AT (1)  AT441460T (en) 
AU (1)  AU2005239691A1 (en) 
CA (1)  CA2531467A1 (en) 
DE (1)  DE602004022964D1 (en) 
DK (1)  DK1674129T3 (en) 
ES (1)  ES2330936T3 (en) 
PT (1)  PT1674129E (en) 
Cited By (12)
Publication number  Priority date  Publication date  Assignee  Title 

WO2007117647A2 (en) *  20060407  20071018  Accuray Incorporated  Automatically determining a beam parameter for radiation treatment planning 
US20080089481A1 (en) *  20061016  20080417  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US20090090870A1 (en) *  20060504  20090409  Scanditronix Wellhofer Ab  Detector response modeling 
WO2009114669A1 (en) *  20080312  20090917  Sun Nuclear Corp.  Radiation therapy plan dose perturbation system and method 
US7693260B2 (en)  20070409  20100406  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US7792249B2 (en)  20071223  20100907  Oraya Therapeutics, Inc.  Methods and devices for detecting, controlling, and predicting radiation delivery 
US7801271B2 (en)  20071223  20100921  Oraya Therapeutics, Inc.  Methods and devices for orthovoltage ocular radiotherapy and treatment planning 
US20110022360A1 (en) *  20090723  20110127  Sun Nuclear Corporation  Multiple axes scanning system and method for measuring radiation from a radiation source 
US8363783B2 (en)  20070604  20130129  Oraya Therapeutics, Inc.  Method and device for ocular alignment and coupling of ocular structures 
US8506558B2 (en)  20080111  20130813  Oraya Therapeutics, Inc.  System and method for performing an ocular irradiation procedure 
CN104857638A (en) *  20140225  20150826  株式会社日立制作所  A beam position monitor and the charged particle beam irradiation system 
US10099067B2 (en)  20141219  20181016  Sun Nuclear Corporation  Radiation therapy dose calculation 
Citations (15)
Publication number  Priority date  Publication date  Assignee  Title 

US4726046A (en) *  19851105  19880216  Varian Associates, Inc.  Xray and electron radiotherapy clinical treatment machine 
US5027818A (en) *  19871203  19910702  University Of Florida  Dosimetric technique for stereotactic radiosurgery same 
US5291404A (en) *  19900418  19940301  Mitsubishi Denki Kabushiki Kaisha  Radiotherapy treatment planning system 
US5317616A (en) *  19920319  19940531  Wisconsin Alumni Research Foundation  Method and apparatus for radiation therapy 
US5528651A (en) *  19940609  19960618  Elekta Instrument Ab  Positioning device and method for radiation treatment 
US5596653A (en) *  19910409  19970121  Mitsubishi Denki Kabushiki Kaisha  Radiation therapy treatment planning system 
US5627367A (en) *  19951010  19970506  Sofield Science Services, Inc.  Radiation beam calibrater 
US6301329B1 (en) *  19980209  20011009  The University Of Southampton  Treatment planning method and apparatus for radiation therapy 
US6345114B1 (en) *  19950614  20020205  Wisconsin Alumni Research Foundation  Method and apparatus for calibration of radiation therapy equipment and verification of radiation treatment 
US6459762B1 (en) *  20010313  20021001  Ro Inventions I, Llc  Method for producing a range of therapeutic radiation energy levels 
US6697452B2 (en) *  20010216  20040224  The Board Of Trustees Of The Leland Stanford Junior University  Verification method of monitor units and fluence map in intensity modulated radiation therapy 
US6714620B2 (en) *  20000922  20040330  Numerix, Llc  Radiation therapy treatment method 
US6882702B2 (en) *  20020429  20050419  University Of Miami  Intensity modulated radiotherapy inverse planning algorithm 
US7046762B2 (en) *  19991105  20060516  Georgia Tech Research Corporation  Systems and methods for global optimization of treatment planning for external beam radiation therapy 
US7289599B2 (en) *  20021004  20071030  Varian Medical Systems Technologies, Inc.  Radiation process and apparatus 
Family Cites Families (4)
Publication number  Priority date  Publication date  Assignee  Title 

JPH0691902B2 (en) *  19900418  19941116  三菱電機株式会社  Radiation treatment planning system 
US6260005B1 (en) *  19960305  20010710  The Regents Of The University Of California  Falcon: automated optimization method for arbitrary assessment criteria 
US6097787A (en) *  19980810  20000801  Siemens Medical Systems, Inc.  System and method for calculating scatter radiation 
AT312648T (en) *  20020617  20051215  Nucletron Bv  System for realtime planning of radiotherapy 

2004
 20041223 DK DK04078493T patent/DK1674129T3/en active
 20041223 AT AT04078493T patent/AT441460T/en unknown
 20041223 PT PT04078493T patent/PT1674129E/en unknown
 20041223 EP EP04078493A patent/EP1674129B1/en not_active Expired  Fee Related
 20041223 ES ES04078493T patent/ES2330936T3/en active Active
 20041223 DE DE602004022964T patent/DE602004022964D1/en active Active

2005
 20051201 AU AU2005239691A patent/AU2005239691A1/en not_active Abandoned
 20051213 US US11/299,891 patent/US7542545B2/en not_active Expired  Fee Related
 20051222 CA CA002531467A patent/CA2531467A1/en not_active Abandoned
 20051222 JP JP2005370530A patent/JP4936723B2/en not_active Expired  Fee Related
Patent Citations (15)
Publication number  Priority date  Publication date  Assignee  Title 

US4726046A (en) *  19851105  19880216  Varian Associates, Inc.  Xray and electron radiotherapy clinical treatment machine 
US5027818A (en) *  19871203  19910702  University Of Florida  Dosimetric technique for stereotactic radiosurgery same 
US5291404A (en) *  19900418  19940301  Mitsubishi Denki Kabushiki Kaisha  Radiotherapy treatment planning system 
US5596653A (en) *  19910409  19970121  Mitsubishi Denki Kabushiki Kaisha  Radiation therapy treatment planning system 
US5317616A (en) *  19920319  19940531  Wisconsin Alumni Research Foundation  Method and apparatus for radiation therapy 
US5528651A (en) *  19940609  19960618  Elekta Instrument Ab  Positioning device and method for radiation treatment 
US6345114B1 (en) *  19950614  20020205  Wisconsin Alumni Research Foundation  Method and apparatus for calibration of radiation therapy equipment and verification of radiation treatment 
US5627367A (en) *  19951010  19970506  Sofield Science Services, Inc.  Radiation beam calibrater 
US6301329B1 (en) *  19980209  20011009  The University Of Southampton  Treatment planning method and apparatus for radiation therapy 
US7046762B2 (en) *  19991105  20060516  Georgia Tech Research Corporation  Systems and methods for global optimization of treatment planning for external beam radiation therapy 
US6714620B2 (en) *  20000922  20040330  Numerix, Llc  Radiation therapy treatment method 
US6697452B2 (en) *  20010216  20040224  The Board Of Trustees Of The Leland Stanford Junior University  Verification method of monitor units and fluence map in intensity modulated radiation therapy 
US6459762B1 (en) *  20010313  20021001  Ro Inventions I, Llc  Method for producing a range of therapeutic radiation energy levels 
US6882702B2 (en) *  20020429  20050419  University Of Miami  Intensity modulated radiotherapy inverse planning algorithm 
US7289599B2 (en) *  20021004  20071030  Varian Medical Systems Technologies, Inc.  Radiation process and apparatus 
Cited By (67)
Publication number  Priority date  Publication date  Assignee  Title 

WO2007117650A3 (en) *  20060407  20080508  Accuray Inc  Automatically determining size or shape of a radiation beam 
WO2007117650A2 (en) *  20060407  20071018  Accuray Incorporated  Automatically determining size or shape of a radiation beam 
US20080011945A1 (en) *  20060407  20080117  Maurer Calvin R Jr  Automatically determining a beam parameter for radiation treatment planning 
US20080013687A1 (en) *  20060407  20080117  Maurer Calvin R Jr  Automatically determining size or shape of a radiation beam 
WO2007117647A2 (en) *  20060407  20071018  Accuray Incorporated  Automatically determining a beam parameter for radiation treatment planning 
US7590219B2 (en)  20060407  20090915  Accuray Incorporated  Automatically determining a beam parameter for radiation treatment planning 
WO2007117647A3 (en) *  20060407  20080515  Accuray Inc  Automatically determining a beam parameter for radiation treatment planning 
US20080123813A1 (en) *  20060407  20080529  Maurer Calvin R  Automatic selection of multiple collimators 
US20090090870A1 (en) *  20060504  20090409  Scanditronix Wellhofer Ab  Detector response modeling 
US8053736B2 (en) *  20060504  20111108  Iba S.A.  Detector response modeling 
US7496174B2 (en)  20061016  20090224  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US20080187100A1 (en) *  20061016  20080807  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US20080089480A1 (en) *  20061016  20080417  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US8995618B2 (en)  20061016  20150331  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US8855267B2 (en)  20061016  20141007  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US7680244B2 (en)  20061016  20100316  Oraya Therapeutics, Inc.  Ocular radiosurgery 
US20080089481A1 (en) *  20061016  20080417  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US7693258B2 (en)  20061016  20100406  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US7693259B2 (en)  20061016  20100406  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8837675B2 (en)  20061016  20140916  Oraya Therapeutics, Inc.  Ocular radiosurgery 
US7697663B2 (en)  20061016  20100413  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8761336B2 (en)  20061016  20140624  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8611497B2 (en)  20061016  20131217  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US7822175B2 (en)  20061016  20101026  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US8442185B2 (en)  20061016  20130514  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US7912178B2 (en)  20061016  20110322  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8320524B2 (en)  20061016  20121127  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8189739B2 (en)  20061016  20120529  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8180021B2 (en)  20061016  20120515  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8094779B2 (en)  20061016  20120110  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8073105B2 (en)  20061016  20111206  Oraya Therapeutics, Inc.  Ocular radiosurgery 
US7680245B2 (en)  20061016  20100316  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8059784B2 (en)  20061016  20111115  Oraya Therapeutics, Inc.  Portable orthovoltage radiotherapy 
US8295437B2 (en)  20061213  20121023  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US7978819B2 (en)  20061213  20110712  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US7961845B2 (en)  20061213  20110614  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8787524B2 (en)  20061213  20140722  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8306186B2 (en)  20061213  20121106  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US9272161B2 (en)  20061213  20160301  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8229073B2 (en)  20061213  20120724  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8229069B2 (en)  20061213  20120724  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8238517B2 (en)  20061213  20120807  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US7978818B2 (en)  20061213  20110712  Oraya Therapeutics, Inc.  Orthovoltage radiotherapy 
US8184772B2 (en)  20070409  20120522  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US7953203B2 (en)  20070409  20110531  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US7912179B2 (en)  20070409  20110322  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US8457277B2 (en)  20070409  20130604  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US7693260B2 (en)  20070409  20100406  Oraya Therapeutics, Inc.  Orthovoltage radiosurgery 
US8363783B2 (en)  20070604  20130129  Oraya Therapeutics, Inc.  Method and device for ocular alignment and coupling of ocular structures 
US8923479B2 (en)  20070604  20141230  Oraya Therapeutics, Inc.  Method and device for ocular alignment and coupling of ocular structures 
US8630388B2 (en)  20070604  20140114  Oraya Therapeutics, Inc.  Method and device for ocular alignment and coupling of ocular structures 
US9025727B2 (en)  20071223  20150505  Oraya Therapeutics, Inc.  Methods and devices for orthovoltage ocular radiotherapy and treatment planning 
US8848869B2 (en)  20071223  20140930  Oraya Therapeutics, Inc.  Methods and devices for detecting, controlling, and predicting radiation delivery 
US7801271B2 (en)  20071223  20100921  Oraya Therapeutics, Inc.  Methods and devices for orthovoltage ocular radiotherapy and treatment planning 
US8494116B2 (en)  20071223  20130723  Oraya Therapeutics, Inc.  Methods and devices for orthovoltage ocular radiotherapy and treatment planning 
US7792249B2 (en)  20071223  20100907  Oraya Therapeutics, Inc.  Methods and devices for detecting, controlling, and predicting radiation delivery 
US8503609B2 (en)  20071223  20130806  Oraya Therapeutics, Inc.  Methods and devices for detecting, controlling, and predicting radiation delivery 
US8512236B2 (en)  20080111  20130820  Oraya Therapeutics, Inc.  System and method for positioning and stabilizing an eye 
US8506558B2 (en)  20080111  20130813  Oraya Therapeutics, Inc.  System and method for performing an ocular irradiation procedure 
US8920406B2 (en)  20080111  20141230  Oraya Therapeutics, Inc.  Device and assembly for positioning and stabilizing an eye 
US20090252292A1 (en) *  20080312  20091008  Sun Nucear, Corp.  Radiation therapy plan dose perturbation system and method 
WO2009114669A1 (en) *  20080312  20090917  Sun Nuclear Corp.  Radiation therapy plan dose perturbation system and method 
US7945022B2 (en)  20080312  20110517  Sun Nuclear Corp.  Radiation therapy plan dose perturbation system and method 
US20110022360A1 (en) *  20090723  20110127  Sun Nuclear Corporation  Multiple axes scanning system and method for measuring radiation from a radiation source 
US8321179B2 (en)  20090723  20121127  Sun Nuclear Corporation  Multiple axes scanning system and method for measuring radiation from a radiation source 
CN104857638A (en) *  20140225  20150826  株式会社日立制作所  A beam position monitor and the charged particle beam irradiation system 
US10099067B2 (en)  20141219  20181016  Sun Nuclear Corporation  Radiation therapy dose calculation 
Also Published As
Publication number  Publication date 

AT441460T (en)  20090915 
JP4936723B2 (en)  20120523 
ES2330936T3 (en)  20091217 
PT1674129E (en)  20091117 
EP1674129A1 (en)  20060628 
DK1674129T3 (en)  20091123 
CA2531467A1 (en)  20060623 
DE602004022964D1 (en)  20091015 
AU2005239691A1 (en)  20060713 
EP1674129B1 (en)  20090902 
JP2006175239A (en)  20060706 
US7542545B2 (en)  20090602 
Similar Documents
Publication  Publication Date  Title 

Blomquist et al.  Test procedures for verification of an electron pencil beam algorithm implemented for treatment planning  
Reynaert et al.  Monte Carlo treatment planning for photon and electron beams  
Bucciolini et al.  Verification of IMRT fields by film dosimetry  
Knoos et al.  Limitations of a pencil beam approach to photon dose calculations in lung tissue  
Ma et al.  Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system  
Chetty et al.  Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning  
US7142634B2 (en)  Radiation field detection  
Neuenschwander et al.  MMCa highperformance Monte Carlo code for electron beam treatment planning  
US6714620B2 (en)  Radiation therapy treatment method  
Tzedakis et al.  Influence of initial electron beam parameters on Monte Carlo calculated absorbed dose distributions for radiotherapy photon beams  
Siebers et al.  A method for photon beam Monte Carlo multileaf collimator particle transport  
Ahnesjo et al.  Determination of effective bremsstrahlung spectra and electron contamination for photon dose calculations  
Chaney et al.  A Monte Carlo study of accelerator head scatter  
Ju et al.  Film dosimetry for intensity modulated radiation therapy: dosimetric evaluation  
Popescu et al.  Absolute dose calculations for Monte Carlo simulations of radiotherapy beams  
Verhaegen et al.  Monte Carlo dosimetry study of a 6 MV stereotactic radiosurgery unit  
Mesoloras et al.  Neutron scattered dose equivalent to a fetus from proton radiotherapy of the mother  
Li et al.  Evaluation of the ArcCHECK QA system for IMRT and VMAT verification  
Klein et al.  Clinical implementation of a commercial multileaf collimator: dosimetry, networking, simulation, and quality assurance  
Fippel et al.  A Monte Carlo dose calculation algorithm for proton therapy  
Miften et al.  Implementation of FFT convolution and multigrid superposition models in the FOCUS RTP system  
Aspradakis et al.  Experimental verification of convolution/superposition photon dose calculations for radiotherapy treatment planning  
US8916842B2 (en)  Hadron treatment planning with adequate biological weighting  
Spezi et al.  A DICOMRTbased toolbox for the evaluation and verification of radiotherapy plans  
Sheikh‐Bagheri et al.  Monte Carlo calculation of nine megavoltage photon beam spectra using the BEAM code 
Legal Events
Date  Code  Title  Description 

AS  Assignment 
Owner name: NUCLETRON B.V., NETHERLANDS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:NYHOLM, TUFVE;OLOFSSON, JORGEN;AHNESJO, ANDERS;AND OTHERS;REEL/FRAME:017680/0366;SIGNING DATES FROM 20060410 TO 20060418 Owner name: NUCLETRON B.V., NETHERLANDS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:NYHOLM, TUFVE;OLOFSSON, JORGEN;AHNESJO, ANDERS;AND OTHERS;REEL/FRAME:017680/0357;SIGNING DATES FROM 20060410 TO 20060418 

AS  Assignment 
Owner name: NUCLETRON OPERATIONS B.V., NETHERLANDS Free format text: CHANGE OF NAME;ASSIGNOR:NUCLETRON B.V.;REEL/FRAME:028539/0494 Effective date: 20120425 

REMI  Maintenance fee reminder mailed  
LAPS  Lapse for failure to pay maintenance fees  
STCH  Information on status: patent discontinuation 
Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362 

FP  Expired due to failure to pay maintenance fee 
Effective date: 20130602 